{"id":"https://openalex.org/W2774201527","doi":"https://doi.org/10.1109/igarss.2017.8127970","title":"Derivation of biophysical parameters from fused remote sensing data","display_name":"Derivation of biophysical parameters from fused remote sensing data","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2774201527","doi":"https://doi.org/10.1109/igarss.2017.8127970","mag":"2774201527"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2017.8127970","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2017.8127970","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108649656","display_name":"Thorsten Dahms","orcid":null},"institutions":[{"id":"https://openalex.org/I25974101","display_name":"University of W\u00fcrzburg","ror":"https://ror.org/00fbnyb24","country_code":"DE","type":"education","lineage":["https://openalex.org/I25974101"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dahms Thorsten","raw_affiliation_strings":["Department of Remote Sensing, University of W\u00fcrzburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Remote Sensing, University of W\u00fcrzburg, Germany","institution_ids":["https://openalex.org/I25974101"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103789917","display_name":"Conrad Christopher","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141069","display_name":"Bochum University of Applied Sciences","ror":"https://ror.org/04x02q560","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210141069"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Conrad Christopher","raw_affiliation_strings":["Hochschule Bochum, Heiligenhaus, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hochschule Bochum, Heiligenhaus, Germany","institution_ids":["https://openalex.org/I4210141069"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112336826","display_name":"Dinesh Kumar Babu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dinesh Kumar Babu","raw_affiliation_strings":["German Remote Sensing Data Center National Ground Segment, Neustrelitz, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"German Remote Sensing Data Center National Ground Segment, Neustrelitz, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065514280","display_name":"Marco Schmidt","orcid":"https://orcid.org/0000-0002-7232-5256"},"institutions":[{"id":"https://openalex.org/I4210141069","display_name":"Bochum University of Applied Sciences","ror":"https://ror.org/04x02q560","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210141069"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Schmidt Marco","raw_affiliation_strings":["Hochschule Bochum, Heiligenhaus, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hochschule Bochum, Heiligenhaus, Germany","institution_ids":["https://openalex.org/I4210141069"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102724890","display_name":"Erik Borg","orcid":"https://orcid.org/0000-0001-8288-8426"},"institutions":[{"id":"https://openalex.org/I25974101","display_name":"University of W\u00fcrzburg","ror":"https://ror.org/00fbnyb24","country_code":"DE","type":"education","lineage":["https://openalex.org/I25974101"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Borg Erik","raw_affiliation_strings":["Department of Remote Sensing, University of W\u00fcrzburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Remote Sensing, University of W\u00fcrzburg, Germany","institution_ids":["https://openalex.org/I25974101"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.9289,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.91810902,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"4374","last_page":"4377"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.98089998960495,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9807999730110168,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.790664553642273},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.720057487487793},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5241718292236328},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.48800769448280334},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.47278571128845215},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.4328458905220032},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.140315443277359},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1143987774848938},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.077818363904953}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.790664553642273},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.720057487487793},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5241718292236328},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.48800769448280334},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.47278571128845215},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.4328458905220032},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.140315443277359},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1143987774848938},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.077818363904953},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2017.8127970","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2017.8127970","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","score":0.7799999713897705,"id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1976355321","https://openalex.org/W1993292319","https://openalex.org/W2001796588","https://openalex.org/W2050225888","https://openalex.org/W2088603520","https://openalex.org/W2104235537","https://openalex.org/W2116730904","https://openalex.org/W2130995459","https://openalex.org/W2263045862","https://openalex.org/W2323776951","https://openalex.org/W2911964244","https://openalex.org/W6640214683"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2121524756","https://openalex.org/W782553550","https://openalex.org/W2633218168","https://openalex.org/W2059707233","https://openalex.org/W4235897794","https://openalex.org/W1983126463","https://openalex.org/W2095126257","https://openalex.org/W2085738998","https://openalex.org/W1987967678"],"abstract_inverted_index":{"Resent":[0],"launches":[1],"of":[2,26,33,39,44,85,99,143,161,168,177,187],"optical":[3,45],"space-borne":[4],"remote":[5,27,48,72,87,179],"sensing":[6,28,49,73,88,180],"systems":[7],"with":[8],"high":[9,11,175],"resolution,":[10],"temporal":[12,125],"repetition":[13],"rate,":[14],"and":[15,56,97,102,117,128,132,198],"constant":[16],"viewing":[17],"angles":[18],"(e.g.:":[19,36,62],"Ven\u03bcs,":[20],"Sentinel-2)":[21],"will":[22],"fortify":[23],"the":[24,31,37,83,95,135,144,162,169,174,188],"potential":[25,176],"applications":[29],"in":[30,90,139,157],"context":[32],"agricultural":[34,91,183],"monitoring":[35],"derivation":[38],"biophysical":[40,145],"parameters).":[41],"The":[42,141,165,185],"practicality":[43],"and/or":[46,124],"thermal":[47],"data":[50,69,89,104,115,126,181],"is":[51],"often":[52],"limited":[53],"by":[54],"tile":[55],"cloud":[57],"coverage.":[58],"Spatial-Temporal-Adaptive":[59],"Fusion":[60],"Model":[61],"STARFM)":[63],"can":[64],"be":[65],"used":[66,111],"to":[67,75,81,120,129,153],"combine":[68],"from":[70],"different":[71,158],"sensors":[74],"overcome":[76],"these":[77],"limitations.":[78],"In":[79,107],"order":[80],"investigate":[82],"reliability":[84],"synthesized":[86,112],"monitoring,":[92],"we":[93,110],"evaluated":[94],"quality":[96,166,186],"integrity":[98],"predicted":[100],"FPAR":[101,131],"LAI":[103,133],"on":[105],"maize.":[106],"this":[108],"context,":[109],"daily":[113],"LANDSAT-like":[114],"products":[116],"a":[118,151],"RandomForest":[119],"fill":[121],"possible":[122],"spatial":[123],"gaps":[127],"predict":[130],"for":[134,182],"entire":[136,170],"growing":[137],"period":[138,172],"2015.":[140],"evaluation":[142],"time":[146],"series":[147],"was":[148],"concluded":[149],"using":[150],"weekly":[152],"bi-weekly":[154],"ground":[155],"measurements":[156],"phenological":[159],"stages":[160],"maize":[163],"plant.":[164],"assessment":[167],"growth":[171],"revealed":[173],"synthetic":[178],"monitoring.":[184],"results":[189],"range":[190],"between":[191],"R2=":[192,199],"0.68;":[193],"RMSE":[194,201],"=":[195,202],"0.79":[196],"(LAI)":[197],"0.76;":[200],"0.12":[203],"(FPAR).":[204]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
